Residential heating and cooling systems consume significant amounts of energy. Accordingly, energy management devices have been designed to regulate the operation of residential heating and cooling systems, in an effort to reduce the energy consumption of these systems. For example, self-contained, programmable thermostats allow consumers to set various heating or cooling setpoints that apply to different times of day.
Due to the generally limited nature of programmable thermostat user interfaces (e.g., small display, few buttons), programming such a thermostat is difficult. Moreover, such user interfaces provide limited functionality for programming and control. For example, a consumer's energy usage patterns may change quite often or in complex ways that are difficult or impossible to describe via a thermostat's user interface. For instance, a given consumer may have a late meeting one weeknight, and on another weekday may be home for the entire day instead of going to work. Setting a conventional thermostat to accommodate these behavioral changes requires a significant amount of programming. As a result, few thermostats are used effectively to reduce residential energy usage.
Systems available to consumers for controlling other residential energy loads are even more limited. Programmable timers can be used to switch on and off energy loads within a residence, but these timers have even more limited user interfaces than programmable thermostats. Programmable timers are typically limited to allowing a consumer to specify a few on and off times of an associated energy consuming device throughout the day. As with programmable thermostats, the ability to link programmable timers to consumers' changing schedules and preferences is unavailable.
In addition, in order to minimize peak usage on energy grids, utility companies have implemented direct control systems for large residential loads, such as heating and cooling systems, water heaters, and pool pumps. However, such direct load control systems usually have little or no consumer involvement. Instead, such systems allow the utility alone to define when a residential load is to be turned off, suiting only the energy reduction needs of the utility.
Existing direct load control systems have several disadvantages. For example, such systems treat each consumer in a given group the same as all other consumers in the group. These systems do not contemplate that each consumer may have different preferences regarding participation in utility-implemented load control events. Nor do these systems have methods whereby consumers can communicate such preferences to the utility. For example, on a given hot afternoon, some consumers in a load control region may be away from home, while others are at home. Even if a utility were able to achieve its desired load reduction by controlling the cooling systems of only those consumers who are away from home, the utility currently lacks techniques for determining such user schedules and/or preferences. Because the utility cannot determine the schedule and/or preferences of each user at a current time, the utility must resort to controlling all of the users in the load control region together. While current systems may allow a consumer to override a load control event once it has been scheduled or implemented, it would be preferable if the user could avoid participating in the load control event based on their status and/or preferences.